Echo planar imaging (EPI) is a fast imaging technique that has been widely used in various MRI applications, such diffusion, perfusion and functional magnetic resonance imaging (fMRI). However, the EPI image quality is intrinsically hindered by three major artifacts, i.e., Nyquist ghost, geometric distortion and fat residue. The main objective of this dissertation is to investigate and develop novel methods to correct different EPI artifacts using parallel imaging.
Firstly, a new Nyquist ghost and geometric distortion correction method using parallel imaging was proposed in EPI. This method calibrates the parallel imaging from two frames of EPI acquired with different phase labels. Then Nyquist ghost is subsequently removed by reconstructing images from only positive or negative echoes. Meanwhile, this phase labeling strategy shifts the TE of the second frame and allows the B0 field map generation from positive and negative images for distortion correction. The phantom results at 7T and 3T demonstrated that our method could greatly reduce Nyquist ghost even under oblique imaging and poor eddy current conditions, yielding significant improvements over the existing reference scan and image entropy minimization methods, and eliminate the geometric distortion simultaneously. The phantom results indicated that the SNR efficiency was largely preserved while the fMRI results showed no apparent degradation of temporal resolution.
Secondly, in order to further improve the SNR performance of parallel imaging in Nyquist ghost correction, a new method which incorporates phase error correction with sensitivity encoding (SENSE) was proposed. This method reconstructs two Nyquist ghost free images from positive or negative echo, and then estimates a phase error map from these two images. Phase error correction is subsequently incorporated into SENSE to reconstruct the final Nyquist ghost free images. Results from phantom and human brain experiments demonstrated that this method was as robust as the other parallel imaging based Nyquist ghost correction techniques even under oblique imaging and poor eddy current conditions. Moreover, SNR measurements in both phantom and in vivo studies suggested that this method did not suffer from noise amplification and provided larger signal-to-noise ratio (SNR) than the others similar parallel imaging based Nyquist ghost correction techniques.
Lastly, the parallel imaging was applied to separate water and fat signal in EPI images. This method utilizes the intrinsic chemical shift property of fat. It treats the water and shifted fat signal in composite EPI images as two simultaneously excited images, which are separated by parallel imaging. Two parallel imaging reconstruction algorithms were applied and evaluated for water and fat separation. The human brain EPI results demonstrated the feasibility of using parallel imaging to separate water and fat signal by both algorithms. This method was further applied to brain and liver diffusion weighted imaging, and the results demonstrated it can be used to remove the undesired fat residual signal.
In summary, these studies have demonstrated parallel imaging can be used for EPI artifacts correction and benefit EPI-based applications.

Echo planar imaging (EPI) is a fast imaging technique that has been widely used in various MRI applications, such diffusion, perfusion and functional magnetic resonance imaging (fMRI). However, the EPI image quality is intrinsically hindered by three major artifacts, i.e., Nyquist ghost, geometric distortion and fat residue. The main objective of this dissertation is to investigate and develop novel methods to correct different EPI artifacts using parallel imaging.
Firstly, a new Nyquist ghost and geometric distortion correction method using parallel imaging was proposed in EPI. This method calibrates the parallel imaging from two frames of EPI acquired with different phase labels. Then Nyquist ghost is subsequently removed by reconstructing images from only positive or negative echoes. Meanwhile, this phase labeling strategy shifts the TE of the second frame and allows the B0 field map generation from positive and negative images for distortion correction. The phantom results at 7T and 3T demonstrated that our method could greatly reduce Nyquist ghost even under oblique imaging and poor eddy current conditions, yielding significant improvements over the existing reference scan and image entropy minimization methods, and eliminate the geometric distortion simultaneously. The phantom results indicated that the SNR efficiency was largely preserved while the fMRI results showed no apparent degradation of temporal resolution.
Secondly, in order to further improve the SNR performance of parallel imaging in Nyquist ghost correction, a new method which incorporates phase error correction with sensitivity encoding (SENSE) was proposed. This method reconstructs two Nyquist ghost free images from positive or negative echo, and then estimates a phase error map from these two images. Phase error correction is subsequently incorporated into SENSE to reconstruct the final Nyquist ghost free images. Results from phantom and human brain experiments demonstrated that this method was as robust as the other parallel imaging based Nyquist ghost correction techniques even under oblique imaging and poor eddy current conditions. Moreover, SNR measurements in both phantom and in vivo studies suggested that this method did not suffer from noise amplification and provided larger signal-to-noise ratio (SNR) than the others similar parallel imaging based Nyquist ghost correction techniques.
Lastly, the parallel imaging was applied to separate water and fat signal in EPI images. This method utilizes the intrinsic chemical shift property of fat. It treats the water and shifted fat signal in composite EPI images as two simultaneously excited images, which are separated by parallel imaging. Two parallel imaging reconstruction algorithms were applied and evaluated for water and fat separation. The human brain EPI results demonstrated the feasibility of using parallel imaging to separate water and fat signal by both algorithms. This method was further applied to brain and liver diffusion weighted imaging, and the results demonstrated it can be used to remove the undesired fat residual signal.
In summary, these studies have demonstrated parallel imaging can be used for EPI artifacts correction and benefit EPI-based applications.

-

dc.language

eng

-

dc.publisher

The University of Hong Kong (Pokfulam, Hong Kong)

-

dc.relation.ispartof

HKU Theses Online (HKUTO)

-

dc.rights

Creative Commons: Attribution 3.0 Hong Kong License

-

dc.rights

The author retains all proprietary rights, (such as patent rights) and the right to use in future works.